Two-thirds of organisations at significant risk of software outage within next year

As businesses accelerate AI development, two-thirds of organisations face a significant risk of software outages in the coming year due to prioritising speed over quality.

According to a new report by testing and quality engineering firm Tricentis, nearly half (45%) of teams are focused on increasing delivery speed, while only 13% are prioritising software quality.

As a result, 66% of global organisations are at high risk of experiencing a software outage within the next 12 months. Alarmingly, over 60% admit to deploying code without fully testing it.

The report, which surveyed more than 2,700 DevOps and quality assurance leaders and software developers worldwide, included input from CIOs, CTOs, and VPs of engineering across sectors such as public services, energy and utilities, manufacturing, and financial services.

This puts companies at risk of security breaches, compliance failures, and increasing technical debt, maintenance costs, and customer churn, the report states.

McDonald’s, Sainsbury’s, and Tesco say IT outages were “unrelated”

An overwhelming 90% of CIOs, CTOs, and delivery teams are confident in AI’s ability to autonomously make software release decisions, and almost 100% see value in autonomous testing for quality assurance.

“Recent software outages caused by unchecked code changes underscore how vital high-quality software is to the broader organisational ecosystem,” said Kevin Thompson, CEO of Tricentis.

“As AI evolves, tech leaders must define what quality means for their organisation, finding the right balance between speed, quality, and cost through comprehensive testing strategies to drive better business outcomes.”

Andrew Power, head of UKI at Tricentis, added that the growing risk of software outages in the UK, now higher than the global average, is increasing the urgency for engineering teams to improve their development processes.

He noted that agentic AI offers a significant opportunity to boost productivity and software quality. By adopting autonomous testing and AI-led delivery tools, organisations can meet tight deadlines without compromising reliability.

The original content of the note was published on Techinformed.com. To read the full note visit here

What software developers need to know about cybersecurity

In 2024, cyber criminals didn’t just knock on the front door—they walked right in. High-profile breaches hit widely used apps from tech giants and consumer platforms alike, including Snowflake, Ticketmaster, AT&T, 23andMe, Trello, and Life360. Meanwhile, a massive, coordinated attack targeting Dropbox, LinkedIn, and X (formerly Twitter) compromised a staggering 26 billion records.

These aren’t isolated incidents—they’re a wake-up call. If reducing software vulnerabilities isn’t already at the top of your development priority list, it should be. The first step? Empower your developers with secure coding best practices. It’s not just about writing code that works—it’s about writing code that holds up under fire.

Start with the known
Before developers can defend against sophisticated zero-day attacks, they need to master the fundamentals—starting with known vulnerabilities. These trusted industry resources provide essential frameworks and up-to-date guidance to help teams code more securely from day one:

OWASP Top 10: The Open Worldwide Application Security Project (OWASP) curates regularly updated Top 10 lists that highlight the most critical security risks across web, mobile, generative AI, API, and smart contract applications. These are must-know threats for every developer.

MITRE: MITRE offers an arsenal of tools to help development teams stay ahead of evolving threats. The MITRE ATT&CK framework details adversary tactics and techniques while CWE (Common Weakness Enumeration) catalogs common coding flaws with serious security implications. MITRE also maintains the CVE Program, an authoritative source for publicly disclosed cybersecurity vulnerabilities.

NIST NVD: The National Institute of Standards and Technology (NIST) maintains the National Vulnerability Database (NVD), a repository of security checklist references, vulnerability metrics, software flaws, and impacted product data.
Training your developers to engage with these resources isn’t just the best practice, it’s your first line of defense.

Standardize on secure coding techniques
Training developers to write secure code shouldn’t be looked at as a one-time assignment. It requires a cultural shift. Start by making secure coding techniques are the standard practice across your team. Two of the most critical (yet frequently overlooked) practices are input validation and input sanitization.

Get access control right
Authentication and authorization aren’t just security check boxes—they define who can access what and how. This includes access to code bases, development tools, libraries, APIs, and other assets.

Don’t forget your APIs
APIs may be less visible, but they form the connective tissue of modern applications. The top security risks? Broken authentication, broken authorization, and lax access controls. Make sure security is baked into API design from the start, not bolted on later.

Assume sensitive data will be under attack
Sensitive data consists of more than personally identifiable information (PII) and payment information. It also includes everything from two-factor authentication (2FA) codes and session cookies to internal system identifiers. If exposed, this data becomes a direct line to the internal workings of an application and opens the door to attackers.

Log and monitor applications
Application logging and monitoring are essential for detecting threats, ensuring compliance, and responding promptly to security incidents and policy violations. Logging is more than a check-the-box activity—for developers, logging can be a critical line of defense.

Integrate security in every phase
You don’t have to compromise security for speed. When effective security practices are baked in across the development process—from planning and architecture to coding, deployment, and maintenance—vulnerabilities can be identified early to ensure a smooth release.

Build on secure foundations
While secure code is important, it’s only part of the equation. The entire SDLC has its own attack surface to manage and defend. Every API, cloud server, container, and microservice adds complexity and provides opportunities for attackers.

In fact, one-third of the most significant application breaches of 2024 resulted from attacks on cloud infrastructure while the rest were traced back to compromised APIs and weak access controls.

Manage third-party risk
So, you’ve implemented best practices across your development environment, but what about your supply chain vendors? Applications are only as secure as their weakest links. Software ecosystems today are interconnected and complex. Third-party libraries, frameworks, cloud services, and open-source components all represent prime entry points for attackers.

A software bill of materials (SBOM) can help you understand what’s under the hood, providing a detailed inventory of application components and libraries to identify potential vulnerabilities.

Commit to continuous monitoring
Application security is a moving target. Tools, threats, dependencies, and even the structure of your teams evolve. Your security posture should evolve with them.

The original content of the note was published on Infoworld.com. To read the full note visit here

If your developments do not meet expectations, it is because you do not have the right equipment.

Creating a successful mobile application goes far beyond having a good idea. It requires planning, strategy and, above all, a development team that understands how to transform your vision into a functional and attractive digital solution. If your developments are not achieving the results you expected, the problem might not be in the idea, but in the team behind it.


Why does your development team make a difference?


App development is not just about writing code. It's a process that involves UX/UI design, software architecture, systems integration, rigorous testing and a growth strategy. An inexperienced or poorly structured team can lead to problems such as:


-Performance failures: apps crashing, consuming too many resources, or not working properly on all devices.
-Poor user experience: Confusing interfaces, unintuitive navigation or lack of end-user optimization.
-Late releases: Teams without an efficient working methodology can delay development, impacting time to market.
-Scalability problems: A poorly built app will not be able to grow with your business, forcing you to redo key parts of the development.


Mobilenik: The team you need to take your app to the next level.


At Mobilenik, we know that the success of an app depends not only on the code, but on the strategy and the team that builds it. We specialize in the development of innovative mobile applications, offering a comprehensive service from ideation to launch and continuous optimization.


Why choose us?


User-centered development
We design apps with a flawless user experience (UX), making sure they are intuitive, engaging and functional.


Cutting-edge technology
We use the most advanced tools and frameworks to ensure fast, secure and scalable applications.


Agile Methodology
We work with agile methodologies to deliver constant advances, adapting quickly to changes and optimizing each phase of development.


Multidisciplinary team
From UX/UI designers to developers and digital strategy specialists, at Mobilenik we bring together the necessary talent to make your app a reality.


It's not just about developing, but about developing well.


If your app doesn't meet expectations, it's time to rethink who is in charge of its development. Mobilenik not only creates apps, but ensures that they are successful from day one.


Ready to boost your app? Contact us HERE and let's work together on a development that really makes a difference.

Software development trends and predictions for 2025

As the world races towards 2025, Developer examines what lies ahead for software development in the new year.

Among the most pressing trends for 2025 are AI development simplification, the integration of cross-functional engineering teams, and the evolution of DevSecOps practices. These shifts promise to redefine how companies approach innovation, security, and efficiency in their development pipelines.

AI-powered development simplification
Avthar Sewrathan, AI Product Lead at Timescale, predicts a significant transformation in the tech stack landscape by 2025.

“The traditional tech stack will continue to collapse,” Sewrathan notes, highlighting advancements driven by APIs and tools that reduce complexity and enable faster development. This shift is anticipated to empower engineers of all skill levels to create impactful AI applications with ease.

“By 2025, the traditional tech stack will continue to collapse, fueled by APIs and tools that reduce complexity and enable faster development,” Sewrathan explains. “Companies that deliver frictionless, accessible solutions with low barriers to entry will empower engineers to create impactful AI apps, no matter their level of expertise.”

Developer role evolution
Indu Keri, General Manager and Head of Engineering for Hybrid Cloud at Nutanix, envisions a new era of software development starting in 2025.

“Software development and engineering is already being democratised with tools like Copilot,” Keri says.

By combining GenAI with low-code solutions, code will be abstracted to the point of irrelevance. AI will generate applications rather than code, enabling developers to step into strategic roles.

“The day-to-day for developers will change drastically,” Keri notes. “No longer hamstrung by grunt work, developers will step into an up-leveled, strategic role—communicating with decision-makers about how tech can solve business problems.”

Agentic AI and DevOps automation
The hype around agentic AI will reach boiling point in 2025 as organisations bundle specialised agents for different stages of software delivery, including code generation, testing, and quality assurance. This orchestrator-driven approach will drive a more intelligent approach to DevOps automation.

Martin Reynolds, Field CTO of Harness, says: “Instead of having one, basic GenAI assistant, organisations will bundle together specialised agents for the different stages of software delivery—such as code generation, testing, and quality assurance.”

Integration of cross-functional engineering teams
Moving beyond AI development, the prediction for cross-functional engineering teams is another area of significant change. Reynolds outlines a future where standalone DevOps teams are phased out in favour of more holistic groups that include representation from all engineering disciplines.

“In 2025, organisations will move away from standalone DevOps teams towards more holistic groups that include representation from all engineering disciplines,” Reynolds explains.

Evolution of DevSecOps practices
The software development landscape is also witnessing a significant evolution in DevSecOps practices.

Dylan Thomas, Senior Director of Product Engineering at OpenText Cybersecurity, predicts that, by 2025, DevSecOps will evolve beyond the “shift-left” paradigm to embrace a more mature “shift everywhere” approach.

This shift will require organisations to apply the right tools at the right stages of the DevSecOps cycle, improving efficiency and effectiveness in security practices.

Software Bill of Materials (SBOM) maturity

One of the critical components in this evolving landscape is the Software Bill of Materials (SBOM).

Government mandates are driving organisations to adopt SBOMs at scale, requiring them not only to generate these documents but also to make them actionable.

PostgreSQL’s role in managing complex data types
PostgreSQL’s extension capabilities are also anticipated to play a significant role in managing complex data types in one place.

“In 2025, PostgreSQL will solidify its position as the go-to ‘everything database’—the first to fully integrate AI functionality like embeddings directly within its core ecosystem,” says Avthar Sewrathan, AI Product Lead at Timescale.

“This will streamline data workflows, eliminate the need for external processing tools, and enable businesses to manage complex data types in one place.”

Diverse app stores will reshape mobile distribution
The app store ecosystem is poised for a significant shift as mobile carriers are expected to regain their influence over app distribution.

Matt Tubergen, EVP of Global Strategy & Partnerships at Digital Turbine, said: “The app store ecosystem is set to shift away from an Apple and Google duopoly to an open landscape as mobile carriers regain the power to connect consumers with apps.”

Emerging regulatory changes are also playing a critical role in leveling the playing field. These include bans that prevent tech giants like Google from incentivising app store preloads, which allow carriers and device manufacturers to preload their own apps on new devices.

Emergence of xOps
The convergence of DevOps, DataOps, and ModelOps into a new “xOps” paradigm is expected as more traditional applications adopt AI capabilities.

“This new-found set of dependencies will dramatically accelerate ‘AI-aware’ Release Orchestration while also challenging operations teams, support teams, QA teams, and more as the line between more traditional declarative applications blur with the new dependencies to LLMs and GenAI capabilities,” explains Derek Holt, CEO of Digital.ai.

Increasing security challenges
While AI-generated code can significantly increase developer efficiency, it also introduces security risks due to increased volume of code that must still be tested for vulnerabilities and errors.

“While research has shown that generative AI can halve the time it takes developers to complete coding tasks, the increased volume of code being produced must still be tested for vulnerabilities and errors,” warns Holt.

“This will increase security risk and lead to additional toil in the later stages of delivery, wiping out any efficiency gains from AI-generated code.”

Heightened regulatory scrutiny
Despite the increasing security challenges, a failure to secure software could have ever more serious repercussions. In light of increasing awareness and demand for reliable software systems, developers must prepare for heightened regulatory scrutiny.

Martin Reynolds, Field CTO of Harness, comments: “In the wake of the CrowdStrike outage, there will be an increase in regulatory pressure around poor-quality software.”

By adopting these strategies, organisations not only bolster software resilience but also enhance trust and brand loyalty among consumers. As regulations evolve to emphasise software reliability akin to cybersecurity standards, being proactive will be key to supporting business growth and staying ahead of regulatory measures. This approach not only mitigates risks but positions companies favorably in a landscape where quality is increasingly synonymous with competitive advantage.

Overall, the predictions for 2025 paint a picture of an industry bracing for radical transformation—driven by advancements in AI development, cross-functional engineering teams, and mature DevSecOps practices. These changes promise to accelerate innovation while enhancing security and user experience across industries.

The original content of the note was published on Developer-tech.com. To read the full note visit here

The secret tool top developers are using to create amazing apps

In the world of mobile application development, standing out is no easy task. With a competitive market and users more demanding than ever, companies need a strategic ally that allows them to create innovative, efficient and memorable apps. This is where Mobilenik comes in, the secret tool that is revolutionizing the way mobile applications are designed and developed.

What makes Mobilenik so special?

Mobilenik is not just a development company; it's a platform that integrates everything you need to transform an idea into a high-impact mobile application. From the first sketch to the final release, Mobilenik prioritizes user experience (UX) and collaboration at every stage of the process.

These are the keys to success with Mobilenik:

1-UX design from day one.

Mobilenik understands that UX design is the heart of any successful app. That's why our approach starts with a thorough analysis of user and customer needs. We create interactive prototypes that allow us to test ideas and optimize the experience before entering the development stage.

With Mobilenik, each application is intuitive, functional and aesthetically impeccable, ensuring that users not only use it, but love it.

2-Real-time collaboration

Our system allows designers, developers and project managers to work together in an integrated environment. This seamless collaboration ensures that all aspects of the project are aligned, minimizing errors and maximizing efficiency.

3-Automation and advanced analytics

Mobilenik includes tools that automate key processes, such as testing and data analysis. This allows us to identify improvements in record time, optimizing performance and ensuring that each application meets the highest quality standards.

Why choose Mobilenik for your next project?

The secret of top developers is to use tools that allow them to focus on what really matters: creating applications that solve problems and exceed user expectations. With Mobilenik, you have access to a team committed to:

-Designing experiences that make a difference.

-Developing custom apps that fit your needs.

-Reducing development times without compromising quality.

Mobilenik is not just a tool; it is your strategic partner in the digital transformation of your business.

A path to amazing applications

The mobile app market is evolving rapidly, and Mobilenik is at the forefront of this transformation. Whether you're creating an app from scratch or redesigning an existing one, our comprehensive approach ensures that every project is a success.

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How AI is Redefining Team Dynamics in Collaborative Software Development

While artificial intelligence is transforming various industries worldwide, its impact on software development is especially significant. AI-powered tools are enhancing code quality and efficiency and redefining how teams work together in collaborative environments. As AI continues to evolve, it's becoming a key player in reconfiguring team dynamics, enhancing productivity, and streamlining communication. This article explores how AI redefines team dynamics in collaborative software development, unlocking new ways of working and shaping the industry's future.

The Shift to AI-Augmented Development

In the past, software development relied heavily on human expertise at every stage, from design and coding to testing and deployment. While this traditional approach has driven significant progress, it faces bottlenecks, including inefficiencies, communication barriers, and human errors. Recent advancements in AI, however, are offering intelligent solutions that effectively address these challenges, transforming how development teams operate.

AI-augmented development redefines team collaboration by automating routine tasks such as bug detection, code reviews, and version control. By handling these repetitive tasks, AI allows developers to focus on more complex, higher-order problems, improving their productivity and efficiency. This automation also promotes effective collaboration by minimizing bottlenecks and reducing the need for constant manual intervention.

Enhancing Cross-Functional Collaboration

AI's impact goes beyond just coding; it's becoming vital for enhancing collaboration among teams, especially in agile development environments. Software development relies heavily on teamwork, shifting responsibilities between developers, testers, product managers, and business users. These teams must interact and communicate effectively to achieve their shared goals. AI tools are helping to break down the traditional silos that often get in the way of effective communication.

For instance, AI-driven project management platforms like Asana and Jira optimize task allocation by analyzing team performance and identifying skill gaps. These platforms predict potential roadblocks and suggest workflows that ensure tasks are assigned to the most appropriate team members, improving project outcomes. AI also assists in forecasting timelines, reducing project delays, and providing data-driven insights that help team leaders make more informed decisions.

Boosting Remote and Distributed Teams

In today’s globalized world, remote work has become the norm for many software development teams. Distributed teams often face challenges related to communication, coordination, and maintaining productivity across time zones. AI is crucial in bridging these gaps and ensuring that remote teams remain as effective as co-located ones.

Additionally, AI is transforming code review processes for remote teams. Tools like Codacy and CodeClimate use machine learning algorithms to automate code reviews, ensuring that teams follow best practices even when senior developers are not immediately available for oversight. This mechanism accelerates the review process and maintains consistency in code quality merged into the project.

AI and Continuous Integration/Continuous Delivery (CI/CD)

One of the most significant shifts AI drives in team dynamics is in continuous integration and continuous delivery (CI/CD). AI-powered tools enhance CI/CD pipelines by automating various aspects of the software development lifecycle, from testing to deployment.

AI-driven CI/CD fosters better collaboration among developers and operations teams (DevOps). By automating routine deployment tasks, AI allows DevOps teams to focus on strategic improvements and infrastructure scalability instead of constantly dealing with deployment issues. This enhances the synergy between development and operations teams, creating a more cohesive workflow that aligns with the project's broader goals.

Democratizing Software Development

As AI increasingly integrates into collaborative development environments, software development becomes more accessible to everyone. AI-powered low-code and no-code platforms are allowing non-developers to contribute to software projects in ways that were previously impossible.

Platforms like OutSystems and Appian use AI to guide users through the software development process, enabling business analysts, project managers, and clients to create functional applications without extensive coding expertise. This democratization shifts the traditional dynamic of software teams, where developers are the sole gatekeepers of technical knowledge. Now, diverse teams can actively participate in the development process, contributing to innovation and bringing new perspectives.

AI as a Team Member: The Rise of AI Pair Programming

One of the most fascinating developments in AI-assisted software development is the concept of AI as a virtual team member. AI pair programming, where a human developer collaborates with an AI tool to write and review code, is gaining traction.

AI is changing traditional team dynamics by being a constant collaborator. It is reducing the need for junior developers to rely heavily on senior colleagues for guidance. AI tools can now provide that guidance in real time, helping to level the playing field and accelerate the onboarding process for new team members.

The Bottom Line

AI is not just a tool for improving efficiency; it fundamentally reshapes how teams collaborate and innovate in software development. By automating routine tasks, enhancing cross-functional communication, and enabling more inclusive and democratized development processes, AI is setting the stage for a new era of teamwork.

As AI continues to advance, the future of collaborative software development looks promising. Human creativity and AI-driven automation will work together to unlock new levels of productivity and innovation. Teams will be able to confidently tackle increasingly complex projects, knowing that AI is there to support them at every turn.

The original content of the note was published on Unite.ai. To read the full note visit here

How to Stay Relevant as a Software Developer

For years and years, we joked about robots taking our jobs one day. “It’s coming,” some warned. Fast-forward to a few years ago when AI exploded seemingly overnight. “It’s here,” those same people said.

Enter budget cuts, mass lay-offs, and software developers the world over echoing a similar sentiment: “What now?”

Here’s the good news: Brands are finding that swapping humans for AI might’ve been premature. Here’s the tricky part: Software developers still must choose to evolve or drown.

How to Make Yourself Invaluable as a Software Developer

Some of us have learned, perhaps the hard way, that while AI is incredible and will only get better, there are some things that will simply turn out better if a human being manages them.

However, we’d also be foolish to deny that things have changed tremendously.

I work with developers every single day, and I wanted to better understand what this evolution has meant for them. What can software engineers do to make themselves irreplaceable in the age of AI?

1.Solve a Problem
We’ve seen that AI is sometimes great for taking over monotonous, manual tasks — for instance, sifting through or generating code.
But you, the software developer, still have an upper hand: You see the bigger picture. The end goal in mind. The target you’re aiming for. This is a skill unique to you.
If you’re not sure if your work is solving a problem, take a step back, look at what you’re doing, and ask yourself, “So what?” If you can’t come up with a clear answer, there’s more work to be done.

2.Make Way for Strategy
Alright, you’re using AI, in some capacity, to solve a problem. You’ve found ways to leverage the technology to save you time. Now, you’re going to use that newly freed up time for… what, exactly?
We’ve established that AI might be sufficient for repetitive tasks we used to do, so your employer might not need you to do that stuff anymore. What do they need you for, then?
Strategy — one of those fluffy, corporate-y buzzwords we love to throw around without assigning any real meaning to it. So, let’s assign meaning!

3.Humanize Your Work
There’s a little thing called AI fatigue that is creeping in. AI fatigue is exactly what it sounds like: Some folks are becoming tired and suspicious of the technology.
There’s something so impersonal, so hollow about a piece of content that was created by AI. There’s no life behind it. No energy. To make matters worse, sometimes, it’s painfully obvious that the brains behind a piece of work was artificial intelligence.

4.Get Specific About What You Do for a Living
It used to be enough to say, “I work in tech.” Then, that became too broad, so we opted for, “I work in Developer Relations” (or something like that). Now, even that isn’t specific enough. For software developers to stay relevant and in demand, they need to be more clear on their position and the value they bring to their organization — or an organization they’re applying to.

An Opportunity to Be Better


“What I love about technology is that it’s boring and stable,” said no software developer ever.

I’d like to think that one thing that draws us to this industry is that it’s ever-evolving. This can feel like a double-edged sword sometimes because change can be hard and scary.

However, change also gives us an opportunity to be better than we were before, and that’s how I believe we should approach AI and how it’s changing the landscape of our careers. Solve a problem, prioritize strategy, humanize your work, and be specific with your role, and you and AI can work together as friends.

The original content of the note was published on Towardsdatascience.com. To read the full note visit here

TuringBots Will Transform The Software Development Lifecycle By 2028

Thanks to TuringBots (AI and generative AI for software development), software development is on the cusp of a transformative change, one that promises to redefine the way development teams collaborate, create, and deploy applications. Picture this: a room full of product owners, subject matter experts, testers, and developers, security and architecture pro’s, all working in harmony with the aid of advanced technology including voice and audio integration, digital boards and more. As each stakeholder expresses requirements, ideas, solutions, the TuringBots are listening, elaborating, generating. This is not a scene from a sci-fi movie; it’s the imminent future of the software development lifecycle (SDLC), projected to unfold by 2028. And it doesn’t have to happen in a (TuringBot) meeting room; it can all be happening on your desktop while you are sitting at your desk. TuringBots today can generate use cases, test cases, designs, code and many more sw assets from your requirements, and can automate pipelines to efficiently deliver those assets in production making it all happen in a few hours or even minutes.

The Invisible And Real-Time SDLC: A New Era Begins

Gone are the days of siloed development processes and delayed feedback loops. The future SDLC is seamlessly integrated and invisible, operating in real time. Teams will no longer face the barriers of traditional software development; instead, they will engage in dynamic collaboration with TuringBots — AI and generative AI entities capable of understanding spoken conversations, natural language text, and low-code and code in many programming languages, and furthermore even able to interpret sketches or ideas jotted down on a board.

Real-Time Reviews And Autonomous Evolution

The process of executing and reviewing development work will be dramatically expedited. Teams will be able to review their creations on the fly, conduct code checks, perform security reviews, and grant approvals in real time. Meanwhile, TuringBots will work in the background, autonomously evolving applications to meet emerging needs and fixing issues before they become problems. This paradigm shift is not merely about speeding up the development process; it’s about enhancing creativity, improving accuracy, and ensuring security in ways we’ve only begun to imagine. By enabling all collaboration and asset generation to occur instantaneously, tested and checked by an ever-vigilant, combined team of humans and TuringBots, the development of new applications will reach speeds previously thought impossible.

The Unimaginable Speed Of App Development

As we look toward this future, it’s clear that the role of developers and IT professionals will evolve. The focus will shift from manual coding to strategic oversight and from problem-solving to creative innovation. TuringBots, with their ability to operate behind the scenes with other TuringBots and collaborate with humans, will become an indispensable ally, ensuring that the SDLC can keep pace with the rapid rate of technological change and the ever-growing demands of consumers and businesses alike.

Architect Approach to TuringBot Concerns

There are still concerns with the development of TuringBots, including hallucination, custom software development and architecture enterprise requirements, and the need to adapt to the changing landscape. To harness the power of TuringBots, teams must prioritize prompt engineering and learn to leverage new technologies such as vector embedding and retrieval augmented generation. Teams have to incorporate architecture and architects into generative AI and enforce security by design through Zero Trust principles, enhanced testing and security policies, and minimum-viable security.

Wrapping It All Up

The vision of an invisible and real-time SDLC facilitated by TuringBots is not a distant dream but an impending reality. By 2028, software development as we know it today will undergo a radical transformation, enabling teams to build new applications at previously unimaginable speeds. This future promises not only to enhance the efficiency and effectiveness of the development process but also to open up new possibilities for innovation and creativity in software creation.

The original content of the note was published on Forbes.com. To read the full note visit here

Six Ways the Software Development Platform can Reduce Developer Burnout

The frantic pace of digitization in the industrial internet of things (IoT) creates steep learning curves for embedded software engineers. Building, integrating and updating industrial software applications without compromising safety, security and performance can feel like working under pressure on constantly shifting sands. It can be demotivating and challenging for even the most experienced professional, impacting innovation and creativity; and burnout is a very present issue estimated to affect four in five software developers.

Reduce Barriers, Reduce Burnout

Reducing barriers without compromising on the quality and complexity of projects can be achieved by choosing a software development platform that supports even the most complex embedded applications’ performance, safety and security needs. Here are six ways that the right platform contributes to reducing developer friction.

1)Never Compromise on Throughput Performance
Throughput performance is the heartbeat of software applications, so don’t compromise on the capability criteria of a preferred software development platform.
Empowering mission-critical applications to thrive in any environment requires high overall OS throughput and near-linear scalability with increased cores. Compromise only kicks the can down the road, and settling for less will mean issues with system capability, speed, and reliability from this point on.

2)Plan to Go Big (Not Go Home)
The best practice software design should always be built for growth. However, scalability can easily be hindered by the limitations of the software development platform, be it curbing expansion or compromising safety and security for progress.
Better development starts with a platform that accommodates seamless scalability as a foundation for future innovations and opportunities. Your future self will thank you for it!

3)Know When Compromise is Not Okay
Time and precision-sensitive applications, where reliability is necessary, not optional — such as surgical and production robotics — add extra pressure for software designers. Hard real-time systems built on a microkernel platform that divides core functionality across separate spaces provide a more stable environment, with absolute reliability and no scope for latency or jitter. In contrast, if you build on a monolithic microkernel, however good the software may be, if the system goes down it all goes down.

4)State-Of-The-Art Tooling
Time pressure is a major contributor to stress and burnout for software developers and teams. Removing needles from the haystack is tiresome work, and dated toolkits can mean more rework and delays. Choosing the right developer tools can accelerate time to market, identify and resolve bugs, optimize development workflows and enhance the overall integrated development environment (IDE). Therefore, take time to investigate and find state-of-the-art tooling designed to help modern developers push the boundaries of innovation.

5)Design for the Future, Today
Feeling anxious about tomorrow’s challenges? Architecting a system with the future in mind means being confident that you have a solid foundation for safety and security now, and ensuring systems remain relevant and robust in the long term.
With today’s pace of change, if you plan to adapt your software for future needs, you will already be doing it tomorrow. And the next day.

6)Skills Development is an Industry Responsibility
The best platform technology is designed to evolve and educate, helping the software developer community to keep pace with the world around it, and offering seamless support regardless of complexity.
Explore the education and support provided by your choice of software development platform provider as a gauge of its commitment to the industry. And choose to work with those that invest in progressing industry talent, research and education, as well as minimizing integration hurdles and empowering innovation, every step of the way.

Choosing the right software development platform gives a firm foundation for getting it right the first time. That means developing with the future in mind and setting up for success, reducing stress and pressure of the work.

The original content of the note was published on Devops.com. To read the full note visit here

How To Accelerate Software Development With Generative AI

In the span of just a few years, generative AI has transformed how organizations build products, create content and resolve problems. The majority of business and technology leaders using GenAI are focusing on efficiency and cost-effectiveness gains, according to a 2024 Deloitte survey, with 91% of respondents reporting that they “expect generative AI to improve their organization’s productivity.”

It’s no replacement for human expertise and execution, but it can take the lead on mundane, repetitive tasks, allowing teams to dedicate more time and energy toward critical thinking, problem-solving and collaboration.

By using GenAI tools on my own development team, I’ve discovered that they are most valuable in two key applications.

-Code suggestion and autocompletion: AI can analyze developers' code as they work, automatically generating recommendations for code snippets or complete functions based on context and input.

-Code analysis and bug detection: Generative AI can quickly review code to detect errors or bugs early in the development process.

Strategies For Implementing AI In Software Development

To maximize the benefits of AI in software development, I recommend the following four strategies.

1-Test And Evaluate Different Tools

2-Create Better Prompts

3-Review Code Carefully

4-Protect Sensitive Data

Set realistic expectations, and use AI tools strategically and thoughtfully—in conjunction with human expertise and oversight—to deliver software solutions more efficiently than ever before.

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